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arXiv · 2508.16350

Multivariate Shared Frailty Cure-Rate models: a focus on Breast Cancer family history

Maria Veronica Vinattieri·Marco Bonetti·Kamila Czene
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Abstract

We discuss a shift in perspective from traditional approaches to breast cancer risk prediction: modelling families rather than individuals as unit of analysis. By investigating the latent familial risk underlying breast cancer diagnoses, we introduce a Multivariate Shared Frailty Cure-Rate model. This model captures the familial risk as a shared frailty among members and explicitly accounts for a fraction of women not susceptible to breast cancer. We aim at identifying the high-risk families to better target screening and prevention, ultimately improving early detection. A comparative analysis with Cox models and univariate models - where a binary risk indicator acts as best guess for the latent high-risk group - is conducted using simulation studies and data from the Swedish Multi-Generational Breast Cancer registry. We demonstrate the critical importance of using complete family history of breast cancer to accurately identify high-risk families and show that the Multivariate Shared Frailty Cure-Rate model, capturing both the fraction of non-susceptible subjects and the survival distribution among susceptibles, enhances explanatory power, improves prediction accuracy, and offers a broader representation of the disease process.

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Maria Veronica Vinattieri, Marco Bonetti, Kamila Czene. 2025-08-22. Multivariate Shared Frailty Cure-Rate models: a focus on Breast Cancer family history. https://arxiv.org/abs/2508.16350

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